Real-time Variable Bit Rate Video Research Articles

Supporting multi-user real-time VBR video service using dynamic bandwidth management based on prediction

Real-time variable bit rate (VBR) video is expected to take a significant portion of multimedia applications. However, plentiful challenges to VBR video service provision have been raised for its characteristic of high traffic abruptness. To support multi-user real-time VBR video transmission with high bandwidth utilization and satisfied quality of service (QoS), this article proposes a practical dynamic bandwidth management scheme. This scheme forecasts future media rate of VBR video by employing time-domain adaptive linear predictor and using media delivery index (MDI) as both QoS measurement and complementary management reference. In addition, to support multi-user application, an adjustment priorities classified strategy is also put forward. Finally, a test-bed based on this management scheme is established. The experimental results demonstrate that the scheme proposed in this article is efficient with bandwidth utilization increased by 20%–60% compared to a fixed service rate and QoS guaranteed.

Supporting Real-Time VBR Video Transport on WiMedia-Based Wireless Personal Area Networks

Ultrawideband (UWB) is an emerging technology that is expected to achieve high data rate with low-power transmission and to enable quality-of-service (QoS)-based multimedia services over wireless personal area networks (WPANs). Currently, WiMedia alliance proposes the physical layer and medium access control (MAC) layer standards for WPANs. Although WiMedia MAC defines the QoS signaling mechanism, it does not specify the resource-allocation algorithm that will eventually provide the QoS guarantee. To address this issue, we first propose a novel traffic predictor for real-time variable bit rate (VBR) videos. Based on the proposed predictor, we then present a dynamic resource-allocation (DRA) algorithm to support real-time VBR video transmission over WiMedia-based WPANs. Simulation results indicate that the proposed traffic predictor and DRA algorithm significantly outperform other existing schemes.

Efficient Traffic Scheduling for Real Time VBR MPEG Video Transmission Over DOCSIS-Based HFC Networks

Data-over-cable service interface specifications (DOCSIS), the de facto standard in the cable industry, defines a scheduling service called real-time polling service (rtPS) to provision quality of service (QoS) transmission of real-time variable bit rate (VBR) videos. However, the rtPS service intrinsically has high latency, which makes it not applicable to real-time traffic transport. In this paper, we present a novel traffic scheduling algorithm for hybrid fiber coax (HFC) networks based on DOCSIS that aims to provide QoS for real-time VBR video transmissions. The novel characteristics of this algorithm, as compared to those described in published literatures, include 1) it predicts the bandwidth requirements for future traffic using a novel traffic predictor designed to provide simple yet accurate online prediction; and 2) it takes the attributes of physical (PHY) layer, media access control (MAC) layer and application layer into consideration. In addition, the proposed traffic scheduling algorithm is completely compatible with the DOCSIS specification and does not require any protocol changes. We analyze the performance of the proposed traffic predictor and traffic scheduling algorithm using real-life MPEG video traces. Simulation results indicate that 1) the proposed traffic predictor significantly outperforms previously published techniques with respect to the prediction error and 2) compared with several existing scheduling algorithms, the proposed traffic scheduling algorithm surpasses other mechanisms in terms of channel utilization, buffer usage, packet delay, and packet loss rate.

Adaptive training and pruning algorithm for variable bit rate video traffic pre diction

An adaptive training and pruning algorithm for variable bit rate(VBR) video traffic prediction is proposed in this paper. By simulation and comparison, the adaptive neural network model proposed in this paper is shown to be promising and practically feasible in obtaining the best adaptive prediction of real-time VBR video traffic.

Rate–distortion model based rate control for real-time VBR video coding and low-delay communications

Abstract Rate control is an important component in a video encoder for data storage or real-time visual communications. In the paper, we will discuss the rate control in MPEG encoder for low-delay real-time video communications over variable bit-rate (VBR) channel. In low-delay video communications, the video transmission is subject not only to the channel rate constraints, but also to the end-to-end delay constraints. In the paper, we employ leaky-bucket model to describe the traffic parameters and monitor the encoder's output. First, an ad hoc bit-allocation method is introduced. Although satisfying the rate constraints perfectly, it provides the objective quality of the decoded image to be just comparable to that of CBR rate control using MPEG2 TM5. Then, a new rate–distortion model is developed, based on which an advanced rate control algorithm is designed, producing almost uniform distortion within a frame as well as consistent video quality between frames. Experimental results show that, when compared to both the MPEG2 TM5 and the proposed ad hoc bit-allocation method, the advanced rate control algorithm maintains not only a constant buffer delay, but also a stable decoded image quality in the scenario of VBR transmission.

Using adaptive linear prediction to support real-time VBR video under RCBR network service model

A dynamic bandwidth allocation strategy to support variable bit rate (VBR) video traffic is proposed. This strategy predicts the bandwidth requirements for future frames using adaptive linear prediction that minimizes the mean square error. The adaptive technique does not require any prior knowledge of the traffic statistics nor assume stationarity. Analyses using six one-half-hour video tracts indicate that prediction errors for the bandwidth required for the next frames and group of pictures (GOP) are almost white noise or short memory. The performance of the strategy is studied using renegotiated constant bit rate (RCBR) network service model and methods that control the tradeoff between the number of renegotiations and network utilization are proposed. Simulation results using MPEG-I video traces for predicting GOP rates show that the queue size is reduced by a factor of 15-160 and the network utilization is increased between 190%-300% as compared to a fixed service rate. Results also show that even when renegotiations occur on the average in tens of seconds, the queue size is reduced by a factor between 16-30.

Novel optical fiber code-division multiple access networks supporting real-time multichannel variable-bit-rate (VBR) video distributions

we design novel code-division multiple access (CDMA) networks which use strict optical orthogonal codes (OOCs) and incoherent optical processing for multichannel variable-bit-rate (VBR) video broadcasting. The proposed techniques possess the characteristics of fast access tunability and bit-rate flexibility. This in turn can facilitate real-time VBR video distributions for entertainment HDTV applications. Compared with conventional OOCs, the use of strict OOCs can ensure both auto- and cross-correlation constraints to be minimum (i.e., "1") for multichannel VBR video broadcasting and high-speed photonic switching applications. A parallel-serial hybrid architecture for all-optical tunable decoders (or encoders) is also presented to strict OOCs, which has a fast reconfiguration time to support real-time video applications in high-speed optical fiber CDMA networks.

The importance of long-range dependence of VBR video traffic in ATM traffic engineering

There has been a growing concern about the potential impact of long-term correlations (second-order statistic) in variable-bit-rate (VBR) video traffic on ATM buffer dimensioning. Previous studies have shown that video traffic exhibits long-range dependence (LRD) (Hurst parameter large than 0.5). We investigate the practical implications of LRD in the context of realistic ATM traffic engineering by studying ATM multiplexers of VBR video sources over a range of desirable cell loss rates and buffer sizes (maximum delays). Using results based on large deviations theory, we introduce the notion of Critical Time Scale (CTS). For a given buffer size, link capacity, and the marginal distribution of frame size, the CTS of a VBR video source is defined as the number of frame correlations that contribute to the cell loss rate. In other words, second-order behavior at the time scale beyond the CTS does not significantly affect the network performance. We show that whether the video source model is Markov or has LRD, its CTS is finite, attains a small value for small buffer, and is a non-decreasing function of buffer size. Numerical results show that (i) even in the presence of LRD , long-term correlations do not have significant impact on the cell loss rate; and (ii) short-term correlations have dominant effect on cell loss rate, and therefore, well-designed Markov traffic models are effective for predicting Quality of Service (QOS) of LRD VBR video traffic. Therefore, we conclude that it is unnecessary to capture the long-term correlations of a real-time VBR video source under realistic ATM buffer dimensioning scenarios as far as the cell loss rates and maximum buffer delays are concerned.